Time-Series Data Chunking for Mobile Asset Management
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Solution Overview
Problem
Industrial assets face challenges in reliable data communication and configuration with remote computing platforms due to stringent requirements such as cost, weight, security, and signal interference, especially when mobile devices experience intermittent connectivity.
Innovation Solution
The development of an Asset Management Platform (AMP) that includes a cloud computing system with modules for data acquisition, analytics, security, and operations, utilizing a communication gateway to facilitate data exchange between industrial assets and remote computing resources, and employing a connectivity module for data communication through virtual networks, even in areas with unreliable connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is transmitted continuously to mobile devices, then data availability is improved, but network bandwidth consumption increases and reliability decreases under intermittent connectivity
Solution Approach 1:
The patent segments continuous data streams into discrete time-series records with incremental identifiers. Each record represents a discrete unit of data that can be independently transmitted, cached, and retrieved. This segmentation allows the system to transmit only new or updated records rather than continuously streaming all data, reducing bandwidth consumption while maintaining data availability through selective retransmission of specific segments when connectivity is restored.
2Reliability
If data is cached locally on mobile devices, then data availability during disconnection is improved, but data consistency and synchronization complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-caching data records with incremental identifiers and timestamps before disconnection occurs. The system proactively stores data in a local database with metadata including version identifiers, allowing the mobile device to have data readily available before needing it. When reconnected, the device uses the pre-established incremental identifier system to efficiently determine what data needs synchronization without complex real-time conflict resolution.
Solution Approach 2:
The patent employs feedback mechanisms where the mobile device reports its last received incremental identifier to the server upon reconnection. The server uses this feedback to determine which new records to transmit, creating a closed-loop synchronization system. This feedback-driven approach simplifies complexity by using a single scalar value (the incremental identifier) to track synchronization state rather than managing complex version vectors or conflict resolution protocols.
3Loss of information
If complete time-series data is transmitted, then data completeness is improved, but transmission time and bandwidth usage increases
Solution Approach 1:
The patent implements dynamic data transmission by adjusting the amount of data sent based on the mobile device's connectivity conditions, cached state, and requested time range. The system dynamically determines the optimal set of records to transmit by comparing the device's last known incremental identifier with the server's current data state, and by considering the device's battery level and network conditions. This dynamic approach ensures data completeness for the requested period while minimizing transmission time and bandwidth usage by sending only necessary increments.
4Ease of operation
If data is optimized for mobile devices, then ease of operation is improved, but data processing complexity at the server increases
Solution Approach 1:
The patent extracts and separates the data optimization logic from the mobile device and places it at the server side. The server extracts only the necessary time-series records based on incremental identifiers, filters, and time ranges, then transmits pre-optimized data to the mobile device. This extraction approach improves ease of operation on the device while concentrating processing complexity at the server, where computational resources are more abundant. The server handles the complex tasks of data selection, filtering, and formatting, delivering ready-to-use data to the mobile application.
Data Source
AI summary
A method includes receiving a stream of time-series data. The time-series data was generated by a data generating device. The stream of time-series data is machine-read to generate index marks. The index marks are for insertion into the stream of time-series data. The index marks indicate events represented by the stream of time-series data. The stream of time series data, including the index marks, is divided into chunks for asynchronous transmission to at least one mobile device.